1) What is Artificial Neural Network?
2) What is the type of problems in which Artificial
Neural Network can be applied.
3) Explain the concept of a Perceptron with a neat
4) Discuss the Perceptron training rule.
5) Under what conditions the perceptron rule fails
and it becomes necessary to apply the delta rule
6) What do you mean by Gradient Descent?
7) Derive the Gradient Descent Rule.
8) What are the conditions in which Gradient
Descent is applied.
9) What are the difficulties in applying Gradient
10)Differentiate between Gradient Descent and
Stochastic Gradient Descent
11)Define Delta Rule.
12)Derive the Backpropagation rule considering the
training rule for Output Unit weights and Training Rule for Hidden Unit weights
13)Write the algorithm for Back propagation.
14) Explain how to learn Multilayer Networks using
Gradient Descent Algorithm.
15)What is Squashing Function?